Abstract
This chapter applies the multilevel regression technique in order to validate the ranking of occupational categories in a reputational scale of social desirability. Such attention to the differences inherent in work roles resumes the topic of the unequal distribution of material and symbolic rewards within societies. A tool widely used by sociologists to grasp the distributive inequalities associated with jobs is the occupational stratification scale or the hierarchical ordering of occupations.
The aim of the model presented in this chapter is to validate an occupational stratification scale constructed in 2007 on the basis of the scale developed by de Lillo-Schizzerotto in 1985. The scale consists of 110 occupational categories constructed as the aggregate of 676 occupations (described in detail) which 2000 interviewees were asked to evaluate in terms of their social desirability. The ordering of the scale is validated through decomposition of the heterogeneity of the evaluations. The multilevel model shows that the 110 categories explain large part of this heterogeneity, also with the socio-demographic characteristics of the interviewees remaining equal.
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Notes
- 1.
Specifically, the Universities of Milano-Bicocca, Piemonte Orientale “Amedeo Avogrado”, “Federico II” of Naples, and Trento.
- 2.
We use the term “social desirability” to denote the concept underlying our scale because we believe that reputational scales measure the objective social advantages and disadvantages associated with occupations (de Lillo and Schizzerotto 1985), and not prestige, as frequently argued (for instance by Treiman 1977). We believe, in fact, that the critique to the functionalist approach about the study of social inequalities is correct when it maintains that interviewees do not judge occupations as socially better in light of norms or values. Consequently, it is entirely misleading to establish an association between the social hierarchy of work roles and some sort of classification of individual abilities and merit (Cobalti and Schizzerotto 1994). Our view is borne out by a study on the criteria used by interviewees to evaluate the social positions of occupations in 2005, which found that prestige was not the only dimension underlying the ratings given to those positions (Arosio and De Luca 2007).
- 3.
For a comparison of the 1985 and 2005 scales which sought to determine whether and how the image of the occupational stratification has changed in Italy over the past twenty years see Sarti and Terraneo (2007).
- 4.
The SIDES2005 stratification scale will be thoroughly described in both theoretical and methodological terms in a book currently being prepared by the teams at the Universities which took part in the PRIN2003 project. Some aspects of the scale have already been discussed in a special issue of Quaderni di Sociologia, 45, 2007.
- 5.
See again note 4.
- 6.
The overall number of occupations reported in the figure is 466, and not the 676 as previously indicated. The reason for the discrepancy is as follows. The research design envisaged that some occupations would be evaluated depending on the kind of contract; instead other occupations would be judged according to whether the incumbent was a man or a woman. During the analysis phase, the occupations subject to multiple evaluation were treated as follows: as regards the employment contract only considered were judgments related to occupations pursued on a permanent basis; as regards the gender of the occupation’s incumbent, the score was obtained as the average of the scores given by male and female respondents. This choice entailed a reduction in the overall number of jobs.
- 7.
A classical example demonstrating the need to consider the contexts within which individuals’ act is provided by education. In a study of the 1970s, conducted using standard regression analysis, Bennett (1976) found a statistically significant relation between the “formal” model of education and better student performance. Subsequently Aitkin et al. (1981) repeated the analyses on the same data controlling for the classes to which the students belonged. The result of inserting a higher level of aggregation was the disappearance of the effect of “formal” teaching on pupil progress. In practice, shown to be more important for student performance were the skills of the teacher (common to all the students in the same class), not the teaching method (Goldstein 1995).
- 8.
Ω u describes the heterogeneity of the distribution of the deviations from the general average of each of the 466 occupations – for example, the extent of the differences among a carpenter, bill poster, newspaper editor – bearing in mind that the score for each occupation derived from 60 evaluations.
- 9.
The percentages measure the intra-unit correlation indicating the ability of the contexts in the different levels to explain variability (Goldstein 1995, Leyland and McLeod 2000).
For instance, on two levels the variability explained by the second level is calculated as \(\rho = \frac{{\Omega _u }}{{\Omega _e + \Omega _u }}\).
- 10.
Detailed information about the models can be obtained from the authors upon request. For technical details see Snijders and Bosker (1999).
- 11.
Similar conclusions have been reached by Meraviglia and Accornero (2007).
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Acknowledgments
We are grateful to Mario Lucchini for his suggestions in regard to multilevel analysis. However, responsibility for any errors or omissions is ours alone.
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Sarti, S., Terraneo, M. (2010). An Application of the Multilevel Regression Technique to Validate a Social Stratification Scale. In: Capecchi, V., Buscema, M., Contucci, P., D'Amore, B. (eds) Applications of Mathematics in Models, Artificial Neural Networks and Arts. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-8581-8_8
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